Information-theoretic semantic multimedia indexing

Magalhães, João and Rüger, Stefan (2007). Information-theoretic semantic multimedia indexing. In: ACM International Conference on Image and Video Retrieval (CIVR), 9-11 Jul 2007, Amsterdam, The Netherlands.

URL: http://doi.acm.org/10.1145/1282280.1282368

Abstract

To solve the problem of indexing collections with diverse text documents, image documents, or documents with both text and images, one needs to develop a model that supports heterogeneous types of documents. In this paper, we show how information theory supplies us with the tools necessary to develop a unique model for text, image, and text/image retrieval. In our approach, for each possible query keyword we estimate a maximum entropy model based on exclusively continuous features that were pre-processed. The unique continuous feature-space of text and visual data is constructed by using a minimum description length criterion to find the optimal feature-space representation (optimal from an information theory point of view). We evaluate our approach in three experiments: only text retrieval, only image retrieval, and text combined with image retrieval.

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